New tools provide a second look at HDV ribozyme structure, dynamics and cleavage

Assessment of Nucleobase Protomeric and Tautomeric States in Nucleic Acid Structures for Interaction Analysis and Structure-Based Ligand Design

With increasing interest in RNA as a therapeutic and a potential target, the role of RNA structures has become more important. Even slight changes in nucleobases, such as modifications or protomeric and tautomeric states, can have a large impact on RNA structure and function, while local environments in turn affect protonation and tautomerization. In this work, the application of empirical tools for pKa and tautomer prediction for RNA modifications was elucidated and compared with ab initio quantum mechanics (QM) methods and expanded toward macromolecular RNA structures, where QM is no longer feasible. In this regard, the Protonate3D functionality within the molecular operating environment (MOE) was expanded for nucleobase protomer and tautomer predictions and applied to reported examples of altered protonation states depending on the local environment. Overall, observations of nonstandard protomers and tautomers were well reproduced, including structural C+G:C(A) and A+GG motifs, several mismatches, and protonation of adenosine or cytidine as the general acid in nucleolytic ribozymes. Special cases, such as cobalt hexamine-soaked complexes or the deprotonation of guanosine as the general base in nucleolytic ribozymes, proved to be challenging. The collected set of examples shall serve as a starting point for the development of further RNA protonation prediction tools, while the presented Protonate3D implementation already delivers reasonable protonation predictions for RNA and DNA macromolecules. For cases where higher accuracy is needed, like following catalytic pathways of ribozymes, incorporation of QM-based methods can build upon the Protonate3D-generated starting structures. Likewise, this protonation prediction can be used for structure-based RNA-ligand design approaches.

RNA tertiary structure modeling with BRiQ potential in CASP15

We describe the modeling method for RNA tertiary structures employed by team AIchemy_RNA2 in the 15th Critical Assessment of Structure Prediction (CASP15). The method consists of the following steps. Firstly, secondary structure information was derived from various manually-verified sources. With this information, the full length RNA was fragmented into structural modules. The structures of each module were predicted and then assembled into the full structure. To reduce the searching conformational space, an RNA structure was organized into an optimal base folding tree. And to further improve the sampling efficiency, the energy surface was smoothed at high temperatures during the Monte Carlo sampling to make it easier to move across the energy barrier. The statistical potential energy function BRiQ was employed during Monte Carlo energy optimization.

Advancing RNA 3D structure prediction: Exploring hierarchical and hybrid approaches in CASP15

In CASP15, we used an integrated hierarchical and hybrid approach to predict RNA structures. The approach involves three steps. First, with the use of physics-based methods, Vfold2D-MC and VfoldMCPX, we predict the 2D structures from the sequence. Second, we employ template-based methods, Vfold3D and VfoldLA, to build 3D scaffolds for the predicted 2D structures. Third, using the 3D scaffolds as initial structures and the predicted 2D structures as constraints, we predict the 3D structure from coarse-grained molecular dynamics simulations, IsRNA and RNAJP. Our approach was evaluated on 12 RNA targets in CASP15 and ranked second among all the 34 participating teams. The result demonstrated the reliability of our method in predicting RNA 2D structures with high accuracy and RNA 3D structures with moderate accuracy. Further improvements in RNA structure prediction for the next round of CASP may come from the incorporation of the physics-based method with machine learning techniques.

RNA tertiary structure prediction using RNAComposer in CASP15

As CASP15 participants, in the new category of 3D RNA structure prediction, we applied expert modeling with the support of our proprietary system RNAComposer. Although RNAComposer is primarily known as an automated web server, its features allow it to be used interactively, for example, for homology-based modeling or assembling models from user-provided structural elements. In the paper, we present various scenarios of applying the system to predict the 3D RNA structures that we employed. Their combination with expert input, comparative analysis of models, and routines to select representative resultant structures form a ready-for-reuse workflow. With selected examples, we demonstrate its application for the in silico modeling of natural and synthetic RNA molecules targeted in CASP15.

RNA tertiary structure prediction in CASP15 by the GeneSilico group: Folding simulations based on statistical potentials and spatial restraints

Ribonucleic acid (RNA) molecules serve as master regulators of cells by encoding their biological function in the ribonucleotide sequence, particularly their ability to interact with other molecules. To understand how RNA molecules perform their biological tasks and to design new sequences with specific functions, it is of great benefit to be able to computationally predict how RNA folds and interacts in the cellular environment. Our workflow for computational modeling of the 3D structures of RNA and its interactions with other molecules uses a set of methods developed in our laboratory, including MeSSPredRNA for predicting canonical and non-canonical base pairs, PARNASSUS for detecting remote homology based on comparisons of sequences and secondary structures, ModeRNA for comparative modeling, the SimRNA family of programs for modeling RNA 3D structure and its complexes with other molecules, and QRNAS for model refinement. In this study, we present the results of testing this workflow in predicting RNA 3D structures in the CASP15 experiment. The overall high score of the computational models predicted by our group demonstrates the robustness of our workflow and its individual components in terms of predicting RNA 3D structures of acceptable quality that are close to the target structures. However, the variance in prediction quality is still quite high, and the results are still too far from the level of protein 3D structure predictions. This exercise led us to consider several improvements, especially to better predict and enforce stacking interactions and non-canonical base pairs.

Advances in chaperone-assisted RNA crystallography using synthetic antibodies

RNA molecules play essential roles in many biological functions, from gene expression regulation, cellular growth, and metabolism to catalysis. They frequently fold into three-dimensional structures to perform their functions. Therefore, determining RNA structure represents a key step for understanding the structure-function relationships and developing RNA-targeted therapeutics. X-ray crystallography remains a method of choice for determining high-resolution RNA structures, but it has been challenging due to difficulties associated with RNA crystallization and phasing. Several natural and synthetic RNA binding proteins have been used to facilitate RNA crystallography. Having unique properties to help crystal packing and phasing, synthetic antibody fragments, specifically the Fabs, have emerged as promising RNA crystallization chaperones, and so far, over a dozen of RNA structures have been solved using this strategy. Nevertheless, multiple steps in this approach need to be improved, including the recombinant expression of these anti-RNA Fabs, to warrant the full potential of these synthetic Fabs as RNA crystallization chaperones. This review highlights the nuts and bolts and recent advances in the chaperone-assisted RNA crystallography approach, specifically emphasizing the Fab antibody fragments as RNA crystallization chaperones.

Modeling the 3D structure and conformational dynamics of very large RNAs using coarse-grained molecular simulations

We describe a computational approach to building and simulating realistic 3D models of very large RNA molecules (>1000 nucleotides) at a resolution of one "bead" per nucleotide. The method starts with a predicted secondary structure and uses several stages of energy minimization and Brownian dynamics (BD) simulation to build 3D models. A key step in the protocol is the temporary addition of a 4 ^th spatial dimension that allows all predicted helical elements to become disentangled from each other in an effectively automated way. We then use the resulting 3D models as input to Brownian dynamics simulations that include hydrodynamic interactions (HIs) that allow the diffusive properties of the RNA to be modelled as well as enabling its conformational dynamics to be simulated. To validate the dynamics part of the method, we first show that when applied to small RNAs with known 3D structures the BD-HI simulation models accurately reproduce their experimental hydrodynamic radii (Rh). We then apply the modelling and simulation protocol to a variety of RNAs for which experimental Rh values have been reported ranging in size from 85 to 3569 nucleotides. We show that the 3D models, when used in BD-HI simulations, produce hydrodynamic radii that are usually in good agreement with experimental estimates for RNAs that do not contain tertiary contacts that persist even under very low salt conditions. Finally, we show that sampling of the conformational dynamics of large RNAs on timescales of 100 µs is computationally feasible with BD-HI simulations.

Dissociative Transition State in Hepatitis Delta Virus Ribozyme Catalysis

Ribonucleases and small nucleolytic ribozymes are both able to catalyze RNA strand cleavage through 2'-O-transphosphorylation, provoking the question of whether protein and RNA enzymes facilitate mechanisms that pass through the same or distinct transition states. Here, we report the primary and secondary 18O kinetic isotope effects for hepatitis delta virus ribozyme catalysis that reveal a dissociative, metaphosphate-like transition state in stark contrast to the late, associative transition states observed for reactions catalyzed by specific base, Zn2+ ions, or ribonuclease A. This new information provides evidence for a discrete ribozyme active site design that modulates the RNA cleavage pathway to pass through an altered transition state.

Predicting higher-order mutational effects in an RNA enzyme by machine learning of high-throughput experimental data

Ribozymes are RNA molecules that catalyze biochemical reactions. Self-cleaving ribozymes are a common naturally occurring class of ribozymes that catalyze site-specific cleavage of their own phosphodiester backbone. In addition to their natural functions, self-cleaving ribozymes have been used to engineer control of gene expression because they can be designed to alter RNA processing and stability. However, the rational design of ribozyme activity remains challenging, and many ribozyme-based systems are engineered or improved by random mutagenesis and selection (in vitro evolution). Improving a ribozyme-based system often requires several mutations to achieve the desired function, but extensive pairwise and higher-order epistasis prevent a simple prediction of the effect of multiple mutations that is needed for rational design. Recently, high-throughput sequencing-based approaches have produced data sets on the effects of numerous mutations in different ribozymes (RNA fitness landscapes). Here we used such high-throughput experimental data from variants of the CPEB3 self-cleaving ribozyme to train a predictive model through machine learning approaches. We trained models using either a random forest or long short-term memory (LSTM) recurrent neural network approach. We found that models trained on a comprehensive set of pairwise mutant data could predict active sequences at higher mutational distances, but the correlation between predicted and experimentally observed self-cleavage activity decreased with increasing mutational distance. Adding sequences with increasingly higher numbers of mutations to the training data improved the correlation at increasing mutational distances. Systematically reducing the size of the training data set suggests that a wide distribution of ribozyme activity may be the key to accurate predictions. Because the model predictions are based only on sequence and activity data, the results demonstrate that this machine learning approach allows readily obtainable experimental data to be used for RNA design efforts even for RNA molecules with unknown structures. The accurate prediction of RNA functions will enable a more comprehensive understanding of RNA fitness landscapes for studying evolution and for guiding RNA-based engineering efforts.

Fundamental studies of functional nucleic acids: aptamers, riboswitches, ribozymes and DNAzymes

This review aims at juxtaposing common versus distinct structural and functional strategies that are applied by aptamers, riboswitches, and ribozymes/DNAzymes. Focusing on recently discovered systems, we begin our analysis with small-molecule binding aptamers, with emphasis on in vitro-selected fluorogenic RNA aptamers and their different modes of ligand binding and fluorescence activation. Fundamental insights are much needed to advance RNA imaging probes for detection of exo- and endogenous RNA and for RNA process tracking. Secondly, we discuss the latest gene expression-regulating mRNA riboswitches that respond to the alarmone ppGpp, to PRPP, to NAD⁺, to adenosine and cytidine diphosphates, and to precursors of thiamine biosynthesis (HMP-PP), and we outline new subclasses of SAM and tetrahydrofolate-binding RNA regulators. Many riboswitches bind protein enzyme cofactors that, in principle, can catalyse a chemical reaction. For RNA, however, only one system (glmS ribozyme) has been identified in Nature thus far that utilizes a small molecule - glucosamine-6-phosphate - to participate directly in reaction catalysis (phosphodiester cleavage). We wonder why that is the case and what is to be done to reveal such likely existing cellular activities that could be more diverse than currently imagined. Thirdly, this brings us to the four latest small nucleolytic ribozymes termed twister, twister-sister, pistol, and hatchet as well as to in vitro selected DNA and RNA enzymes that promote new chemistry, mainly by exploiting their ability for RNA labelling and nucleoside modification recognition. Enormous progress in understanding the strategies of nucleic acids catalysts has been made by providing thorough structural fundaments (e.g. first structure of a DNAzyme, structures of ribozyme transition state mimics) in combination with functional assays and atomic mutagenesis.

De novo computational RNA modeling into cryo-EM maps of large ribonucleoprotein complexes

Increasingly, cryo-electron microscopy (cryo-EM) is used to determine the structures of RNA-protein assemblies, but nearly all maps determined with this method have biologically important regions where the local resolution does not permit RNA coordinate tracing. To address these omissions, we present de novo ribonucleoprotein modeling in real space through assembly of fragments together with experimental density in Rosetta (DRRAFTER). We show that DRRAFTER recovers near-native models for a diverse benchmark set of RNA-protein complexes including the spliceosome, mitochondrial ribosome, and CRISPR-Cas9-sgRNA complexes; rigorous blind tests include yeast U1 snRNP and spliceosomal P complex maps. Additionally, to aid in model interpretation, we present a method for reliable in situ estimation of DRRAFTER model accuracy. Finally, we apply DRRAFTER to recently determined maps of telomerase, the HIV-1 reverse transcriptase initiation complex, and the packaged MS2 genome, demonstrating the acceleration of accurate model building in challenging cases.

Effects of flanking regions on HDV cotranscriptional folding kinetics

Hepatitis delta virus (HDV) ribozyme performs the self-cleavage activity through folding to a double pseudoknot structure. The folding of functional RNA structures is often coupled with the transcription process. In this work, we developed a new approach for predicting the cotranscriptional folding kinetics of RNA secondary structures with pseudoknots. We theoretically studied the cotranscriptional folding behavior of the 99-nucleotide (nt) HDV sequence, two upstream flanking sequences, and one downstream flanking sequence. During transcription, the 99-nt HDV can effectively avoid the trap intermediates and quickly fold to the cleavage-active state. It is different from its refolding kinetics, which folds into an intermediate trap state. For all the sequences, the ribozyme regions (from 1 to 73) all fold to the same structure during transcription. However, the existence of the 30-nt upstream flanking sequence can inhibit the ribozyme region folding into the active native state through forming an alternative helix Alt1 with the segments 70-90. The longer upstream flanking sequence of 54 nt itself forms a stable hairpin structure, which sequesters the formation of the Alt1 helix and leads to rapid formation of the cleavage-active structure. Although the 55-nt downstream flanking sequence could invade the already folded active structure during transcription by forming a more stable helix with the ribozyme region, the slow transition rate could keep the structure in the cleavage-active structure to perform the activity.

Evidence That Nucleophile Deprotonation Exceeds Bond Formation in the HDV Ribozyme Transition State

Steric constraints imposed by the active sites of protein and RNA enzymes pose major challenges to the investigation of structure-function relationships within these systems. As a strategy to circumvent such constraints in the HDV ribozyme, we have synthesized phosphoramidites from propanediol derivatives and incorporated them at the 5'-termini of RNA and DNA oligonucleotides to generate a series of novel substrates with nucleophiles perturbed electronically through geminal fluorination. In nonenzymatic, hydroxide-catalyzed intramolecular transphosphorylation of the DNA substrates, pH-rate profiles revealed that fluorine substitution reduces the maximal rate and the kinetic p K_a, consistent with the expected electron-withdrawing effect. In HDV ribozyme reactions, we observed that the RNA substrates undergo transphosphorylation relatively efficiently, suggesting that the conformational constraints imposed by a ribofuranose ring are not strictly required for ribozyme catalysis. In contrast to the nonenzymatic reactions, however, substrate fluorination modestly increases the ribozyme reaction rate, consistent with a mechanism in which (1) the 2'-hydroxyl nucleophile exists predominantly in its neutral, protonated form in the ground state and (2) the 2'-hydroxyl bears some negative charge in the rate-determining step, consistent with a transition state in which the extent of 2'-OH deprotonation exceeds the extent of P-O bond formation.

RNA Structural Dynamics As Captured by Molecular Simulations: A Comprehensive Overview

With both catalytic and genetic functions, ribonucleic acid (RNA) is perhaps the most pluripotent chemical species in molecular biology, and its functions are intimately linked to its structure and dynamics. Computer simulations, and in particular atomistic molecular dynamics (MD), allow structural dynamics of biomolecular systems to be investigated with unprecedented temporal and spatial resolution. We here provide a comprehensive overview of the fast-developing field of MD simulations of RNA molecules. We begin with an in-depth, evaluatory coverage of the most fundamental methodological challenges that set the basis for the future development of the field, in particular, the current developments and inherent physical limitations of the atomistic force fields and the recent advances in a broad spectrum of enhanced sampling methods. We also survey the closely related field of coarse-grained modeling of RNA systems. After dealing with the methodological aspects, we provide an exhaustive overview of the available RNA simulation literature, ranging from studies of the smallest RNA oligonucleotides to investigations of the entire ribosome. Our review encompasses tetranucleotides, tetraloops, a number of small RNA motifs, A-helix RNA, kissing-loop complexes, the TAR RNA element, the decoding center and other important regions of the ribosome, as well as assorted others systems. Extended sections are devoted to RNA-ion interactions, ribozymes, riboswitches, and protein/RNA complexes. Our overview is written for as broad of an audience as possible, aiming to provide a much-needed interdisciplinary bridge between computation and experiment, together with a perspective on the future of the field.

MolProbity: More and better reference data for improved all-atom structure validation

This paper describes the current update on macromolecular model validation services that are provided at the MolProbity website, emphasizing changes and additions since the previous review in 2010. There have been many infrastructure improvements, including rewrite of previous Java utilities to now use existing or newly written Python utilities in the open-source CCTBX portion of the Phenix software system. This improves long-term maintainability and enhances the thorough integration of MolProbity-style validation within Phenix. There is now a complete MolProbity mirror site at http://molprobity.manchester.ac.uk. GitHub serves our open-source code, reference datasets, and the resulting multi-dimensional distributions that define most validation criteria. Coordinate output after Asn/Gln/His "flip" correction is now more idealized, since the post-refinement step has apparently often been skipped in the past. Two distinct sets of heavy-atom-to-hydrogen distances and accompanying van der Waals radii have been researched and improved in accuracy, one for the electron-cloud-center positions suitable for X-ray crystallography and one for nuclear positions. New validations include messages at input about problem-causing format irregularities, updates of Ramachandran and rotamer criteria from the million quality-filtered residues in a new reference dataset, the CaBLAM Cα-CO virtual-angle analysis of backbone and secondary structure for cryoEM or low-resolution X-ray, and flagging of the very rare cis-nonProline and twisted peptides which have recently been greatly overused. Due to wide application of MolProbity validation and corrections by the research community, in Phenix, and at the worldwide Protein Data Bank, newly deposited structures have continued to improve greatly as measured by MolProbity's unique all-atom clashscore.

Genetic diversity and worldwide distribution of the deltavirus genus: A study of 2,152 clinical strains

Hepatitis delta virus (HDV) is responsible for the most severe form of acute and chronic viral hepatitis. We previously proposed that the Deltavirus genus is composed of eight major clades. However, few sequences were available to confirm this classification. Moreover, little is known about the structural and functional consequences of HDV variability. One practical consequence is the failure of most quantification assays to properly detect or quantify plasmatic HDV RNA. Between 2001 and 2014, 2,152 HDV strains were prospectively collected and genotyped in our reference laboratory by means of nucleotide sequencing and extensive phylogenetic analyses of a 400-nucleotide region of the genome (R0) from nucleotides 889 to 1289 encompassing the 3' end of the delta protein-coding gene. In addition, the full-length genome sequence was generated for 116 strains selected from the different clusters, allowing for in-depth characterization of the HDV genotypes and subgenotypes. This study confirms that the HDV genus is composed of eight genotypes (HDV-1 to HDV-8) defined by an intergenotype similarity >85% or >80%, according to the partial or full-length genome sequence, respectively. Furthermore, genotypes can be segregated into two to four subgenotypes, characterized by an intersubgenotype similarity >90% (>84% for HDV-1) over the whole genome sequence. Systematic analysis of genome and protein sequences revealed highly conserved functional nucleotide and amino acid motifs and positions across all (sub)genotypes, indicating strong conservatory constraints on the structure and function of the genome and the protein.

CONCLUSION

This study provides insight into the genetic diversity of HDV and a clear view of its geographical localization and allows speculation as to the worldwide spread of the virus, very likely from an initial African origin. (Hepatology 2017;66:1826-1841).

Development of Site-Specific Mg(2+)-RNA Force Field Parameters: A Dream or Reality? Guidelines from Combined Molecular Dynamics and Quantum Mechanics Simulations

The vital contribution of Mg²⁺ ions to RNA biology is challenging to dissect at the experimental level. This calls for the integrative support of atomistic simulations, which at the classical level are plagued by limited accuracy. Indeed, force fields intrinsically neglect nontrivial electronic effects that Mg²⁺ exerts on its surrounding ligands in varying RNA coordination environments. Here, we present a combined computational study based on classical molecular dynamics (MD) and Density Functional Theory (DFT) calculations, aimed at characterizing (i) the performance of five Mg²⁺ force field (FF) models in RNA systems and (ii) how charge transfer and polarization affect the binding of Mg²⁺ ions in different coordination motifs. As a result, a total of ∼2.5 μs MD simulations (100/200 ns for each run) for two prototypical Mg²⁺-dependent ribozymes showed remarkable differences in terms of populations of inner-sphere coordination site types. Most importantly, complementary DFT calculations unveiled that differences in charge transfer and polarization among recurrent Mg²⁺-RNA coordination motifs are surprisingly small. In particular, the charge of the Mg²⁺ ions substantially remains constant through different coordination sites, suggesting that the common philosophy of developing site-specific Mg²⁺ ion parameters is not in line with the physical origin of the Mg²⁺-RNA MD simulations inaccuracies. Overall, this study constitutes a guideline for an adept use of current Mg²⁺ models and provides novel insights for the rational development of next-generation Mg²⁺ FFs to be employed for atomistic simulations of RNA.

How to understand atomistic molecular dynamics simulations of RNA and protein-RNA complexes?

We provide a critical assessment of explicit-solvent atomistic molecular dynamics (MD) simulations of RNA and protein/RNA complexes, written primarily for non-specialists with an emphasis to explain the limitations of MD. MD simulations can be likened to hypothetical single-molecule experiments starting from single atomistic conformations and investigating genuine thermal sampling of the biomolecules. The main advantage of MD is the unlimited temporal and spatial resolution of positions of all atoms in the simulated systems. Fundamental limitations are the short physical time-scale of simulations, which can be partially alleviated by enhanced-sampling techniques, and the highly approximate atomistic force fields describing the simulated molecules. The applicability and present limitations of MD are demonstrated on studies of tetranucleotides, tetraloops, ribozymes, riboswitches and protein/RNA complexes. Wisely applied simulations respecting the approximations of the model can successfully complement structural and biochemical experiments. WIREs RNA 2017, 8:e1405. doi: 10.1002/wrna.1405 For further resources related to this article, please visit the WIREs website.

'Z-DNA like' fragments in RNA: a recurring structural motif with implications for folding, RNA/protein recognition and immune response

Since the work of Alexander Rich, who solved the first Z-DNA crystal structure, we have known that d(CpG) steps can adopt a particular structure that leads to forming left-handed helices. However, it is still largely unrecognized that other sequences can adopt ‘left-handed’ conformations in DNA and RNA, in double as well as single stranded contexts. These ‘Z-like’ steps involve the coexistence of several rare structural features: a C2’-endo puckering, a syn nucleotide and a lone pair–π stacking between a ribose O4’ atom and a nucleobase. This particular arrangement induces a conformational stress in the RNA backbone, which limits the occurrence of Z-like steps to ≈0.1% of all dinucleotide steps in the PDB. Here, we report over 600 instances of Z-like steps, which are located within r(UNCG) tetraloops but also in small and large RNAs including riboswitches, ribozymes and ribosomes. Given their complexity, Z-like steps are probably associated with slow folding kinetics and once formed could lock a fold through the formation of unique long-range contacts. Proteins involved in immunologic response also specifically recognize/induce these peculiar folds. Thus, characterizing the conformational features of these motifs could be a key to understanding the immune response at a structural level.

Secondary structure confirmation and localization of Mg2+ ions in the mammalian CPEB3 ribozyme

Most of today's knowledge of the CPEB3 ribozyme, one of the few small self-cleaving ribozymes known to occur in humans, is based on comparative studies with the hepatitis delta virus (HDV) ribozyme, which is highly similar in cleavage mechanism and probably also in structure. Here we present detailed NMR studies of the CPEB3 ribozyme in order to verify the formation of the predicted nested double pseudoknot in solution. In particular, the influence of Mg(2+), the ribozyme's crucial cofactor, on the CPEB3 structure is investigated. NMR titrations, Tb(3+)-induced cleavage, as well as stoichiometry determination by hydroxyquinoline sulfonic acid fluorescence and equilibrium dialysis, are used to evaluate the number, location, and binding mode of Mg(2+)ions. Up to eight Mg(2+)ions interact site-specifically with the ribozyme, four of which are bound with high affinity. The global fold of the CPEB3 ribozyme, encompassing 80%-90% of the predicted base pairs, is formed in the presence of monovalent ions alone. Low millimolar concentrations of Mg(2+)promote a more compact fold and lead to the formation of additional structures in the core of the ribozyme, which contains the inner small pseudoknot and the active site. Several Mg(2+)binding sites, which are important for the functional fold, appear to be located in corresponding locations in the HDV and CPEB3 ribozyme, demonstrating the particular relevance of Mg(2+)for the nested double pseudoknot structure.

A Two-Metal-Ion-Mediated Conformational Switching Pathway for HDV Ribozyme Activation

RNA enzymes serve as a potentially powerful platform from which to design catalysts and engineer new biotechnology. A fundamental understanding of these systems provides insight to guide design. The hepatitis delta virus ribozyme (HDVr) is a small, self-cleaving RNA motif widely distributed in nature, that has served as a paradigm for understanding basic principles of RNA catalysis. Nevertheless, questions remain regarding the precise roles of divalent metal ions and key nucleotides in catalysis. In an effort to establish a reaction mechanism model consistent with available experimental data, we utilize molecular dynamics simulations to explore different conformations and metal ion binding modes along the HDVr reaction path. Building upon recent crystallographic data, our results provide a dynamic model of the HDVr reaction mechanism involving a conformational switch between multiple non-canonical G25:U20 base pair conformations in the active site. These local nucleobase dynamics play an important role in catalysis by modulating the metal binding environments of two Mg²⁺ ions that support catalysis at different steps of the reaction pathway. The first ion plays a structural role by inducing a base pair flip necessary to obtain the catalytic fold in which C75 moves towards to the scissile phosphate in the active site. Ejection of this ion then permits a second ion to bind elsewhere in the active site and facilitate nucleophile activation. The simulations collectively describe a mechanistic scenario that is consistent with currently available experimental data from crystallography, phosphorothioate substitutions, and chemical probing studies. Avenues for further experimental verification are suggested.

Assessment of metal-assisted nucleophile activation in the hepatitis delta virus ribozyme from molecular simulation and 3D-RISM

The hepatitis delta virus ribozyme is an efficient catalyst of RNA 2'-O-transphosphorylation and has emerged as a key experimental system for identifying and characterizing fundamental features of RNA catalysis. Recent structural and biochemical data have led to a proposed mechanistic model whereby an active site Mg(2+) ion facilitates deprotonation of the O2' nucleophile, and a protonated cytosine residue (C75) acts as an acid to donate a proton to the O5' leaving group as noted in a previous study. This model assumes that the active site Mg(2+) ion forms an inner-sphere coordination with the O2' nucleophile and a nonbridging oxygen of the scissile phosphate. These contacts, however, are not fully resolved in the crystal structure, and biochemical data are not able to unambiguously exclude other mechanistic models. In order to explore the feasibility of this model, we exhaustively mapped the free energy surfaces with different active site ion occupancies via quantum mechanical/molecular mechanical (QM/MM) simulations. We further incorporate a three-dimensional reference interaction site model for the solvated ion atmosphere that allows these calculations to consider not only the rate associated with the chemical steps, but also the probability of observing the system in the presumed active state with the Mg(2+) ion bound. The QM/MM results predict that a pathway involving metal-assisted nucleophile activation is feasible based on the rate-controlling transition state barrier departing from the presumed metal-bound active state. However, QM/MM results for a similar pathway in the absence of Mg(2+) are not consistent with experimental data, suggesting that a structural model in which the crystallographically determined Mg(2+) is simply replaced with Na(+) is likely incorrect. It should be emphasized, however, that these results hinge upon the assumption of the validity of the presumed Mg(2+)-bound starting state, which has not yet been definitively verified experimentally, nor explored in depth computationally. Thus, further experimental and theoretical study is needed such that a consensus view of the catalytic mechanism emerges.

Computational Methods for RNA Structure Validation and Improvement

With increasing recognition of the roles RNA molecules and RNA/protein complexes play in an unexpected variety of biological processes, understanding of RNA structure-function relationships is of high current importance. To make clean biological interpretations from three-dimensional structures, it is imperative to have high-quality, accurate RNA crystal structures available, and the community has thoroughly embraced that goal. However, due to the many degrees of freedom inherent in RNA structure (especially for the backbone), it is a significant challenge to succeed in building accurate experimental models for RNA structures. This chapter describes the tools and techniques our research group and our collaborators have developed over the years to help RNA structural biologists both evaluate and achieve better accuracy. Expert analysis of large, high-resolution, quality-conscious RNA datasets provides the fundamental information that enables automated methods for robust and efficient error diagnosis in validating RNA structures at all resolutions. The even more crucial goal of correcting the diagnosed outliers has steadily developed toward highly effective, computationally based techniques. Automation enables solving complex issues in large RNA structures, but cannot circumvent the need for thoughtful examination of local details, and so we also provide some guidance for interpreting and acting on the results of current structure validation for RNA.

New insights into Hoogsteen base pairs in DNA duplexes from a structure-based survey

Hoogsteen (HG) base pairs (bps) provide an alternative pairing geometry to Watson-Crick (WC) bps and can play unique functional roles in duplex DNA. Here, we use structural features unique to HG bps (syn purine base, HG hydrogen bonds and constricted C1'-C1' distance across the bp) to search for HG bps in X-ray structures of DNA duplexes in the Protein Data Bank. The survey identifies 106 A•T and 34 G•C HG bps in DNA duplexes, many of which are undocumented in the literature. It also uncovers HG-like bps with syn purines lacking HG hydrogen bonds or constricted C1'-C1' distances that are analogous to conformations that have been proposed to populate the WC-to-HG transition pathway. The survey reveals HG preferences similar to those observed for transient HG bps in solution by nuclear magnetic resonance, including stronger preferences for A•T versus G•C bps, TA versus GG steps, and also suggests enrichment at terminal ends with a preference for 5'-purine. HG bps induce small local perturbations in neighboring bps and, surprisingly, a small but significant degree of DNA bending (∼14°) directed toward the major groove. The survey provides insights into the preferences and structural consequences of HG bps in duplex DNA.

Inverse thio effects in the hepatitis delta virus ribozyme reveal that the reaction pathway is controlled by metal ion charge density

The hepatitis delta virus (HDV) ribozyme self-cleaves in the presence of a wide range of monovalent and divalent ions. Prior theoretical studies provided evidence that self-cleavage proceeds via a concerted or stepwise pathway, with the outcome dictated by the valency of the metal ion. In the present study, we measure stereospecific thio effects at the nonbridging oxygens of the scissile phosphate under a wide range of experimental conditions, including varying concentrations of diverse monovalent and divalent ions, and combine these with quantum mechanical/molecular mechanical (QM/MM) free energy simulations on the stereospecific thio substrates. The R_P substrate gives large normal thio effects in the presence of all monovalent ions. The S_P substrate also gives normal or no thio effects, but only for smaller monovalent and divalent cations, such as Li⁺, Mg²⁺, Ca²⁺, and Sr²⁺; in contrast, sizable inverse thio effects are found for larger monovalent and divalent cations, including Na⁺, K⁺, NH₄⁺, and Ba²⁺. Proton inventories are found to be unity in the presence of the larger monovalent and divalent ions, but two in the presence of Mg²⁺. Additionally, rate–pH profiles are inverted for the low charge density ions, and only imidazole plus ammonium ions rescue an inactive C75Δ variant in the absence of Mg²⁺. Results from the thio effect experiments, rate–pH profiles, proton inventories, and ammonium/imidazole rescue experiments, combined with QM/MM free energy simulations, support a change in the mechanism of HDV ribozyme self-cleavage from concerted and metal ion-stabilized to stepwise and proton transfer-stabilized as the charge density of the metal ion decreases.